In this paper we ask if, and to what extent, successful collaboration between artificial agents on complex situated tasks can emerge even from minimal, distributed on-the-fly coordination processes. Traditionally, collaboration in artificial agents has been approached as planning problem that must be solved either in a centralized or decentralized fashion [1]}.
Enabling complex collaborative tasks with real-time on-the-fly coordination between autonomous agents, however, is still a challenge and usually requires approximations or heuristic processes.
One reason for this is that both generating accurate action predictions for other agents using a full-blown ToM and optimal planning in complex, dynamic environments are too costly to be performed online [2]}, [3]}.
Simplifications are thus commonplace. It is for this reason that, e.g., most artificial agents perform best in simulations in which the other agents are very similar to themselves (as found in [4]}).
